Sparse nonnegative matrix factorization with the elastic net
Nonnegative matrix factorization is used extensively for feature extraction and clustering analysis. Recently many sparsity/sparseness constraints, such as L1 penalty, are introduced for sparse nonnegative matrix factorization. Inspired by sparsity measures from linear regression model, this paper proposes to integrate nonnegative matrix factorization with another sparsity constraint, the elastic net. The experimental results of clustering analysis on three gene expression datasets demonstrate the effectiveness of the proposed method.
Clustering analysis, Gene expression data, Nonnegative matrix factorization, Sparsity penalty
Liu, Weixiang, Songfeng Zheng, Sen Jia, Linlin Shen, and Xianghua Fu. "Sparse nonnegative matrix factorization with the elastic net." In 2010 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), pp. 265-268. IEEE, 2010.
Proceedings - 2010 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2010